Tableau 8.2 with the new feature 'Story Points' was recently released - and great things are in store for data visualizers and story tellers!

At its core, Story Points is a tool for better communicating and sharing your insights and discoveries with your audience. It basically lets you construct a presentation where you can build a narrative while still taking advantage of all the interactivity. You as the presenter or the audience as explorer can filter, zoom, select data, and access tooltip information and underlying data just as if it were a normal workbook. Only now it will be packaged in a presentation format with a narrative structure and layout defined by you as an author - pretty nifty! The narrative may be your story of the discoveries and conclusions you have made while working with the data, or it may be more of a guided tour through the information.

When hearing about governmental politics, we encounter a lot of information, some official - some from different observers and commentators. We frequently hear about internal turmoil or even crises in the government, and from time to time we see a minister leaving or switching office for one reason or another. Such changes are, of course, recorded in official annals and publications - but rarely do we take the time to actually put a visual face and pattern on this data. If we could do that, it might prompt us to ask other - perhaps more interesting - questions - and hopefully, get interesting answers. In today's post, we will use Tableau to make a little data journalistic attempt at visualizing political data.

The effect of applying design principles to your data visualization.

If you popped by this blog, chances are that you work with BI or data analysis or just find visualization of data interesting. You probably see many visualizations everyday - perhaps you even make some of them yourself. But dealing with a visualization, how do you know if it contains C.R.A.P. or the opposite? That's todays topic.

Don't care about your data and message? Go cook up a pie - your audience will adore you and your work! Or will they - and should they? In todays post we will serve you some pie, discuss pros and cons of this chart type, and offer you a few tips on how to obtain a healthier diet.

The pie chart remains a surprisingly popular ingredient in the media and various sorts of business reports and dashboards. Do a quick Google search on 'Chart' and the menu will look something like this:

Text is an indispensible helper when we make data visualizations, but we need to be careful not to let it steal the picture.

Quartz recently had a short article on the state of residential property prices around the world. The focus was on the wide disparities in price changes within each country between on the one hand, the national average, and on the other hand, the prices in the largest city. The article suggests that generally property prices tend to rise more in the largest city than in the given country as a whole. And that some anomalies can be spotted to that trend in recent figures - presumably the result of regional economic crises.

The article featured this visualization, making use of text, color and position.

Remaking charts has become increasingly popular around the web lately. Good blogs such as JunkCharts, Story Telling With Data, ExcelCharts or The Functional Art all testify to this trend. It is fully understandable! Picking a visualization and working with it is a great way of learning, practising and discussing visualization techniques and generally putting your tools and skills to the test.

I teach people about data visualization - but I will always be a student myself! There is so much interesting stuff out there (yes, a lot of horrible stuff too) and the

Dots don't just look great on Tour de France jersies - they are also great for conveying information in your visualizations in a simple way.

In the
previous post, I created a simple graphic table as an example of how to visualize the overall standing in the Tour de France. I used a dot plot to display a set of values across categories - specifically, the times of the top 10 riders.

In today's post I will revisit the dot plot with two purposes. First, I want to touch upon the virtues of this type of chart by discussing why I chose to use the dot plot as opposed to another type of chart.

Far too often, we seem overly worried that our audience will not find our data interesting and entertaining. So what do we do? We dress up the data with a plethora of appealing and salient visual effects. Effects that, sadly, end up distorting and blurring the very essense of the message we were trying to communicate in the first place.

Taking an interest in data visualization, I took this snapshot of a table shown on a television channel that covered the
Tour de France event.